Opportunities and challenges for ChatGPT and large language models in biomedicine and health
ChatGPT has drawn considerable attention from both the general public and domain experts
with its remarkable text generation capabilities. This has subsequently led to the emergence …
with its remarkable text generation capabilities. This has subsequently led to the emergence …
Artificial intelligence in action: addressing the COVID-19 pandemic with natural language processing
The COVID-19 (coronavirus disease 2019) pandemic has had a significant impact on
society, both because of the serious health effects of COVID-19 and because of public …
society, both because of the serious health effects of COVID-19 and because of public …
MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval
Motivation Information retrieval (IR) is essential in biomedical knowledge acquisition and
clinical decision support. While recent progress has shown that language model encoders …
clinical decision support. While recent progress has shown that language model encoders …
[HTML][HTML] Graph embedding-based link prediction for literature-based discovery in Alzheimer's Disease
Objective: We explore the framing of literature-based discovery (LBD) as link prediction and
graph embedding learning, with Alzheimer's Disease (AD) as our focus disease context. The …
graph embedding learning, with Alzheimer's Disease (AD) as our focus disease context. The …
Exploring the in-context learning ability of large language model for biomedical concept linking
The biomedical field relies heavily on concept linking in various areas such as literature
mining, graph alignment, information retrieval, question-answering, data, and knowledge …
mining, graph alignment, information retrieval, question-answering, data, and knowledge …
A survey of the recent trends in deep learning for literature based discovery in the biomedical domain
Every day, enormous amounts of biomedical texts discussing various biomedical topics are
produced. Revealing strong semantic connections hidden in those unstructured data is …
produced. Revealing strong semantic connections hidden in those unstructured data is …
Scientific language models for biomedical knowledge base completion: an empirical study
Biomedical knowledge graphs (KGs) hold rich information on entities such as diseases,
drugs, and genes. Predicting missing links in these graphs can boost many important …
drugs, and genes. Predicting missing links in these graphs can boost many important …
Scientometric analysis and knowledge mapping of literature-based discovery (1986–2020)
A Kastrin, D Hristovski - Scientometrics, 2021 - Springer
Literature-based discovery (LBD) aims to discover valuable latent relationships between
disparate sets of literatures. This paper presents the first inclusive scientometric overview of …
disparate sets of literatures. This paper presents the first inclusive scientometric overview of …
A literature embedding model for cardiovascular disease prediction using risk factors, symptoms, and genotype information
Accurate prediction of cardiovascular disease (CVD) requires multifaceted information
consisting of not only a patient's medical history, but genomic data, symptoms, lifestyle, and …
consisting of not only a patient's medical history, but genomic data, symptoms, lifestyle, and …
BioREx: improving biomedical relation extraction by leveraging heterogeneous datasets
Biomedical relation extraction (RE) is the task of automatically identifying and characterizing
relations between biomedical concepts from free text. RE is a central task in biomedical …
relations between biomedical concepts from free text. RE is a central task in biomedical …